Update README.md

README.md

@@ -16,7 +16,7 @@ tags:
 
 # Mono-InternVL-2B
 
-[\[⭐️Project Page\]](https://internvl.github.io/blog/2024-10-10-Mono-InternVL/) [\[📜 Mono-InternVL Paper\]](https://arxiv.org/abs/2410.TODO)  [\[🚀 Quick Start\]](#quick-start)
+[\[⭐️Project Page\]](https://internvl.github.io/blog/2024-10-10-Mono-InternVL/) [\[📜 Mono-InternVL Paper\]](https://arxiv.org/abs/2410.08202)  [\[🚀 Quick Start\]](#quick-start)
 
 [切换至中文版](#简介)
 
@@ -38,7 +38,7 @@ Mono-InternVL achieves superior performance compared to state-of-the-art MLLM Mi
 
 
 
-This repository contains the instruction-tuned Mono-InternVL-2B model. It is built upon [internlm2-chat-1_8b](https://huggingface.co/internlm/internlm2-chat-1_8b). For more details, please refer to our [paper](https://arxiv.org/abs/2410.TODO).
+This repository contains the instruction-tuned Mono-InternVL-2B model. It is built upon [internlm2-chat-1_8b](https://huggingface.co/internlm/internlm2-chat-1_8b). For more details, please refer to our [paper](https://arxiv.org/abs/2410.08202).
 
 
 
@@ -222,7 +222,7 @@ If you find this project useful in your research, please consider citing:
 @article{luo2024mono,
   title={Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training},
   author={Luo, Gen and Yang, Xue and Dou, Wenhan and Wang, Zhaokai and Dai, Jifeng and Qiao, Yu and Zhu, Xizhou},
-  journal={arXiv preprint arXiv:2410.TODO},
+  journal={arXiv preprint arXiv:2410.08202},
   year={2024}
 }
 
@@ -252,7 +252,7 @@ If you find this project useful in your research, please consider citing:
 
 Mono-InternVL在性能上优于当前最先进的MLLM Mini-InternVL-2B-1.5，并且显著超越了其他单体化MLLMs，如上方的[雷达图](#radar)所示。同时，它的部署效率也得到了提升，首个token的延迟降低了最多达67%。
 
-本仓库包含了经过指令微调的Mono-InternVL-2B模型，它是基于[internlm2-chat-1_8b](https://huggingface.co/internlm/internlm2-chat-1_8b)搭建的。更多详细信息，请参阅我们的[论文](TODO)。
+本仓库包含了经过指令微调的Mono-InternVL-2B模型，它是基于[internlm2-chat-1_8b](https://huggingface.co/internlm/internlm2-chat-1_8b)搭建的。更多详细信息，请参阅我们的[论文](https://arxiv.org/abs/2410.08202)。
 
 
 
@@ -310,7 +310,7 @@ Mono-InternVL在性能上优于当前最先进的MLLM Mini-InternVL-2B-1.5，并
 @article{luo2024mono,
   title={Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training},
   author={Luo, Gen and Yang, Xue and Dou, Wenhan and Wang, Zhaokai and Dai, Jifeng and Qiao, Yu and Zhu, Xizhou},
-  journal={arXiv preprint arXiv:2410.TODO},
+  journal={arXiv preprint arXiv:2410.08202},
   year={2024}
 }